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Introduction With the explosive growth of microblogging services, short text messages (also known as tweets) are being created and shared at an unprecedented rate. Tweets in its raw form can be incredibly informative, but also overwhelming. Plowing through so many tweets for interesting contents would be a nightmare, not to mention the enormous noises and redundancies that one could encounter. 3

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Conclusion Proposed a prototype called Sumblr which supported continuous tweet stream summarization. Sumblr employed a tweet stream clustering algorithm to compress tweets into TCVs and maintain them in an online fashion. Used a TCV-Rank summarization algorithm for generating online summaries and historical summaries with arbitrary time durations. The topic evolvement could be detected automatically, allowing Sumblr to produce dynamic timelines for tweet streams. For future work, we aim to develop a multi-topic version of Sumblr in a distributed system, and evaluate it on more complete and large- scale datasets. 21